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Time-series data—measurements of a quantity over time—can be presented as stocks (the quantity at each point in time) or flows (the change in quantity from one point in time to the next). In a series of six experiments, we find that the choice of presenting data as stocks or flows can have a consequential impact on judgments. The same data can lead to positive or negative assessments when presented as stocks versus flows and can engender optimistic or pessimistic forecasts for the future. For example, when employment data from 2007 to 2013 are shown as flows (jobs created or lost), President Obama’s impact on the economy during his first year in office is viewed positively, whereas when the same data are shown as stocks (total jobs), his impact is viewed negatively. The results highlight a challenge that accompanies the growing reliance on data and analytics for decision making within organizations: seemingly benign choices—such as that between two informationally equivalent data presentations—can substantively impact how data are interpreted and used, even though the underlying information is the same.